Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 4+ years building automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering...
- Education
- B.S. or M.S. in CS, EE, CE, or equivalent experience
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Role Summary
The engineer will help evolve NVIDIA’s production workflow infrastructure for large-scale chip engineering into a clearer, observable control-plane platform. The role supports workflows spanning configuration, generated artifacts, tool execution, distributed jobs, validation, and shared project state, while working with senior platform and flow architects and users.
What You'll Do
- Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl...
- Model workflow stages, inputs, outputs, validation signals, generated files, dependencies, status, and ownership in configuration and...
- Create machine-readable check results, run manifests, provenance records, log summaries, and status outputs
- Strengthen early-failure checks for missing files, stale generated data, invalid configuration, environment setup, scheduler issues, and...
- Add and test integrations with distributed job execution, shared compute, filesystem state, data-fidelity tracking, and dependency tracing
- Reproduce failures, trace configuration behavior, improve diagnostics, update documentation, and preserve existing workflows
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Strong Linux fundamentals; practical programming experience in Python, Perl, Go, C++, or similar; comfortable reading and modifying Make, YAML, JSON, and shell-based infrastructure; ability to reason about configuration layers, generated files, schemas, validation rules, compatibility, and incremental migration of legacy systems; strong debugging habits, clear written communication, and experience improving production infrastructure without destabilizing active users.
Required
- Strong Linux fundamentals, including shell debugging, environment setup, filesystem behavior, process execution, logs, exit codes, and...
- Practical programming experience in Python, Perl, Go, C++, or similar
- Comfortable reading and modifying Make, YAML, JSON, and shell-based infrastructure
- Ability to reason carefully about configuration layers, generated files, schemas, validation rules, compatibility, and incremental...
- Strong debugging habits, clear written communication, and experience improving production infrastructure without destabilizing active users
Preferred
- Exposure to semiconductor design or EDA workflows, especially RTL, synthesis, place-and-route, timing, signoff, ECO, or handoff flows
- Background with workflow engines, build systems, CI/CD platforms, job schedulers, deployment automation, data pipelines, or large-scale...
- Experience improving legacy Make, Perl, shell, Python, or Tcl systems while preserving existing behavior
- Experience creating structured logs, JSON/YAML schemas, validation frameworks, provenance tracking, dashboards, or observability tools
- Background with shared filesystems, partial writes, stale state, locking, reproducibility, generated artifacts, batch jobs, tests,...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA is building the next generation of production workflow infrastructure for large-scale chip engineering. This platform turns intent, layered configuration, generated files, tool execution, distributed jobs, validation checks, and shared project state into observable, repeatable workflows.
This role is for a systems-minded engineer who may not have prior chip-design or CAD-flow experience, but has strong fundamentals in Linux, automation, configuration systems, scripting, and production infrastructure. You will work alongside senior platform and flow architects to evolve existing Tcl, Make, Perl, Python, YAML, and job-launch infrastructure into a clearer control-plane platform for complex engineering workflows.
What You'll Be Doing:
Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl checks, and structured output files
Help model workflow stages, inputs, outputs, validation signals, generated files, dependencies, status, and ownership in configuration and manifests
Create machine-readable check results, run manifests, provenance records, log summaries, and status outputs that make behavior easier to inspect and debug
Strengthen early-failure checks for missing files, stale generated data, invalid configuration, bad environment setup, scheduler issues, and incomplete run state
Add and test integrations with distributed job execution, shared compute, filesystem state, data-fidelity tracking, and dependency tracing
Work with senior engineers and users to reproduce failures, trace configuration behavior, improve diagnostics, update documentation, and preserve existing workflows
What We Need To See:
B.S. or M.S. in CS, EE, CE, or equivalent experience
4+ years building automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering productivity tools
Strong Linux fundamentals, including shell debugging, environment setup, filesystem behavior, process execution, logs, exit codes, and background jobs
Practical programming experience in Python, Perl, Go, C++, or similar, and comfortable reading and modifying Make, YAML, JSON, and shell-based infrastructure
Ability to reason carefully about configuration layers, generated files, schemas, validation rules, compatibility, and incremental migration of legacy systems
Strong debugging habits, clear written communication, and experience improving production infrastructure without destabilizing active users
Ways To Stand Out From The Crowd:
Exposure to semiconductor design or EDA workflows, especially RTL, synthesis, place-and-route, timing, signoff, ECO, or handoff flows
Background with workflow engines, build systems, CI/CD platforms, job schedulers, deployment automation, data pipelines, or large-scale engineering automation
Experience improving legacy Make, Perl, shell, Python, or Tcl systems while preserving existing behavior
Experience creating structured logs, JSON/YAML schemas, validation frameworks, provenance tracking, dashboards, or observability tools
Background with shared filesystems, partial writes, stale state, locking, reproducibility, generated artifacts, batch jobs, tests, migrations, documentation, or debug tooling
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.